Age and adult attachment style predict psychological distress in the Singapore general population during COVID-19.

To date, there is increasing evidence to suggest that age and adult attachment styles, such as secure, anxious and avoidant attachment are predictive or protective for psychological distress. The study aimed to investigate the extent to which age and adult attachment style, measured by the Attachment Style Questionnaire, predicted psychological distress, measured by the Kessler 10 Psychological Distress Scale, in the Singapore general population during COVID-19. Ninety-nine residents of Singapore (44 females, 52 males, 3 prefer not to state their gender) aged between 18 and 66 completed an online survey, which collected information on age, adult attachment styles and levels of psychological distress. Multiple regression analysis was performed to study the influence of predictive factors on psychological distress. The study identified 20.2%, 13.1% and 14.1% of participants reporting psychological distress at the mild, moderate and severe levels, respectively. The study also reported that age and psychological distress were negatively correlated, and that psychological distress was negatively correlated with both anxious and avoidant attachment styles. It was concluded that age and adult attachment style significantly predicted psychological distress in the Singapore general population during COVID-19. Further studies exploring other variables and risk factors are required to further consolidate these results. At the global level, these findings may help countries predict residents' reactions to future outbreaks and help them prepare strategies and approaches to address these situations.

A Survey of the Various Methods and Models Used to Detect Long COVID

Long-COVID or post-COVID is a phenomenon where people who have recovered from the COVID-19, suffer persisting symptoms for more than 4 weeks after the confirmed case of COVID-19 and they can last for months. Approximately 20% of the people affected by this Coronavirus disease (COVID-19) are suffering from mid and long term effects known as the Long COVID and it can affect multiple organs in the body and this can lead to death. To date, different studies and researches have been undertaken to understand about the Long COVID and make robust estimates on the predicting factors, symptoms and also to assess the various long term effects on the patients affected by it. Based on the available research articles and the papers published in mainstream journals on Long COVID, this survey paper aims at analyzing various methods and Machine learning models used to detect and predict Long COVID, to help clinicians and researchers working on early diagnosis of Long COVID. © 2022 IEEE.

Adverse effects of personnel protective equipment among first line COVID-19 healthcare professionals: A survey in Southern Tunisia.

BACKGROUND: Health care professionals (HCP) were obliged to wear personal protective equipment (PPE) during pandemic in order to minimize the risk of transmission of the emerging virus. The objective of the study was to estimate the prevalence of adverse effects related to the wear of PPE among HCP and to determinate their predictive factors. METHODS: This was a cross-sectional study including a representative sample of 300 randomized HCP at Hedi Chaker University Hospital Sfax, Tunisia, during the period August-September 2021. Data collection was carried out by an anonymous self-administered questionnaire. RESULTS: PPE related adverse effects were noted among 87 HCP with a prevalence of 57.2%. Multivariate analysis showed that factors independently associated with PPE adverse effects were female gender (Adjusted Odds Ratio (AOR) = 1.8; p = 0.048), chronic diseases (AOR = 0.29; p = 0.001) and previous infection with COVID-19 (AOR = 0.46; p = 0.004). Frequent use of bleach or other disinfection product without protection and use of hot water at work were independently associated with a high risk of adverse effects ((AOR = 2.22; p = 0.003) and (AOR = 2.83; p = 0.005), respectively). Similarly, a duration of use of PPE>4 h per day (AOR = 1.98; p = 0.039), as well as use of visors and/or glasses (AOR = 1.84; p = 0.045) were independently associated with PPE related adverse effects. CONCLUSION: The prevalence of adverse effects related to the wear of PPE was alarmingly high among HCP. Multiple risk factors were highlighted, notably professional aspects. Adequate and repetitive training for caregivers on the correct use of PPE remain essential to manage this problem.

Predictive Factors of Suicidal Ideation in Spanish University Students: A Health, Preventive, Social, and Cultural Approach.

Suicide, as the ultimate expression of suicidal ideation, has accompanied human beings throughout history within specific social and cultural contexts. However, in recent decades the increase in suicides, especially in developed countries after the Second Demographic Transition and the rise of postmaterialist values, has been increasing in the youth population. This study is created from a quantitative perspective and aims to determine the predictors of suicidal ideation in university students in Spain. The fieldwork was carried out in a large sample of Spanish universities over several weeks in 2022, with the participation of hundreds of university students (n = 1472). The predictors of suicidal ideation were gender, types of social relationships, history of bullying, health status, taking antidepressant medication, increased anxiety after COVID-19, economic difficulties in continuing studies, and perspective on their future. The results highlight the need for the greater involvement of universities by establishing programs for preventing, detecting, and treating suicidal ideation, always in coordination with health systems to prevent further suicides in their university community.

Digital Self-Efficacy Predictors in Students from a Private University in Peru: A Diagnostic Study in the Context of Virtual Education

The present study aims to analyze the predictive factors of the digital self-efficacy in students from a private university of Lima (Peru) in the context of the Covid-19 pandemic. The sample was 102 university students (92 women (90.2%) and 10 men (9.8%)) between 19 and 40 years old (Mage = 26.39, SD = 7.75). The results show in the analysis with the Student's T the digital self-efficacy is higher in provinces students (Mean = 5.12, p <.01) and lower in the capital city students (Mean = 4.65, p <.05). Then, the correlation analysis shows age, origin place, academic performance and cognitive engagement are related with student digital self-efficacy. Finally, the analysis of multiple lineal regressions between age, origin place, academic performance and cognitive engagement shows only the age predicts positively the digital self-efficacy (β =.28, p<.01). © 2022 IEEE.

Cytokine levels associated with favorable clinical outcome in the CAPSID randomized trial of convalescent plasma in patients with severe COVID-19.

Objectives: To determine the profile of cytokines in patients with severe COVID-19 who were enrolled in a trial of COVID-19 convalescent plasma (CCP). Methods: Patients were randomized to receive standard treatment and 3 CCP units or standard treatment alone (CAPSID trial, ClinicalTrials.gov NCT04433910). The primary outcome was a dichotomous composite outcome (survival and no longer severe COVID-19 on day 21). Time to clinical improvement was a key secondary endpoint. The concentrations of 27 cytokines were measured (baseline, day 7). We analyzed the change and the correlation between serum cytokine levels over time in different subgroups and the prediction of outcome in receiver operating characteristics (ROC) analyses and in multivariate models. Results: The majority of cytokines showed significant changes from baseline to day 7. Some were strongly correlated amongst each other (at baseline the cluster IL-1ß, IL-2, IL-6, IL-8, G-CSF, MIP-1α, the cluster PDGF-BB, RANTES or the cluster IL-4, IL-17, Eotaxin, bFGF, TNF-α). The correlation matrix substantially changed from baseline to day 7. The heatmaps of the absolute values of the correlation matrix indicated an association of CCP treatment and clinical outcome with the cytokine pattern. Low levels of IP-10, IFN-γ, MCP-1 and IL-1ß on day 0 were predictive of treatment success in a ROC analysis. In multivariate models, low levels of IL-1ß, IFN-γ and MCP-1 on day 0 were significantly associated with both treatment success and shorter time to clinical improvement. Low levels of IP-10, IL-1RA, IL-6, MCP-1 and IFN-γ on day 7 and high levels of IL-9, PDGF and RANTES on day 7 were predictive of treatment success in ROC analyses. Low levels of IP-10, MCP-1 and high levels of RANTES, on day 7 were associated with both treatment success and shorter time to clinical improvement in multivariate models. Conclusion: This analysis demonstrates a considerable dynamic of cytokines over time, which is influenced by both treatment and clinical course of COVID-19. Levels of IL-1ß and MCP-1 at baseline and MCP-1, IP-10 and RANTES on day 7 were associated with a favorable outcome across several endpoints. These cytokines should be included in future trials for further evaluation as predictive factors.

Clinical and paraclinical indicators to evaluate the prognosis of COVID-19: Lessons from a case

The coronavirus is a disease that affects the respiratory system, it comes from the SARS-CoV-2 virus that belongs to the Beta coronavirus group and is currently the cause of a high mortality rate worldwide. The diagnosis through images and oropharyngeal and nasopharyngeal tests helps in the recognition of this respiratory condition. We present a clinical case of a 74-year-old patient with diarrhea, dyspnea, and cough, establishing the diagnosis of COVID-19. We found clinical and paraclinical parameters such as advanced age, history of arterial hypertension, dyspnea, low oxygen saturation, increased azoados, increased hepatic enzymes (AST), leukocytosis, lymphopenia, neutrophilia, increased PCR and procalcitonin, plaquetopenia, increased lactic dehydrogenase, increased ferritin, pulmonary infiltrates with a frosted glass appearance evidenced in the X-ray and CT scan of the chest;all these determining factors of unfavorable prognosis according to current scientific evidence. The results of the case analysis are discussed. © 2022 Academia Nacional de Medicina. All rights reserved.

Prevalence and Factors Affecting Willingness to Accept or Refuse Vaccination against COVID-19 among Healthcare Professionals in Southern Tunisia.

BACKGROUND: The COVID-19 pandemic continues to spread throughout the world causing serious morbidity and mortality. Health care professionals (HCP) are on the front line in the face of this pandemic and are identified as priorities for COVID-19 vaccination. This study aimed to estimate the acceptability rate of the COVID-19 vaccination among HCP and to identify their predisposing factors. Methods: This was a cross-sectional study using an anonymous self-administered questionnaire including a randomized sample of HCP in Southern Tunisia, on March-April 2021. Results: Among 300 participants, the COVID-19 vaccine acceptability rate was 65.3%. Factors independently associated with vaccine acceptability were age groups <30 years [Adjusted Odds Ratio (AOR)=4.36; p = 0.002)], urbanity of residence (AOR = 3.44; p = 0.027), medical professional category (AOR = 2.69; p = 0.023) and caring for coronavirus infected patients (AOR = 2.32; p = 0.047). Belief that COVID-19 vaccination is important to work safely as a health care provider (AOR = 3.26; p = 0.013), should be available for all HCP (AOR = 17.98; p = 0.004) and has been quickly developed before it has been thoroughly vetted and tested for efficacy and safety (AOR = 5.88; p < 0.01) were independently associated with willingness to accept vaccine. Planning to get a COVID-19 vaccine for the next years and recommending it to the family were independent predictive factors of accepting COVID-19 vaccine ((AOR = 6.88; p < 0.001) and (AOR = 25.03; p < 0.001), respectively).Conclusion: The acceptance rate of vaccination against COVID-19 among Tunisian HCP is still low in South Tunisian hospitals. Socio-demographic, cultural and professional factors predisposing to the vaccination willingness were highlighted. Combating the vaccine hesitancy of HCP through enhancing sensibilization campaigns is essential to promote vaccination in general population.

Predictive Factors of Extubation Failure in COVID-19 Mechanically Ventilated Patients.

Purpose: We investigated whether COVID-19 patients on mechanical ventilation (MV) had a different extubation outcome compared to non-COVID-19 patients while identifying predictive factors of extubation failure in the former. Methods: A retrospective, single-center, and observational study was done on 216 COVID-19 patients admitted to an intensive care unit (ICU) between March 2020 and March 2021, aged ≥ 18 years, in use of invasive MV for more than 24 h, which progressed to weaning. The primary outcome that was evaluated was extubation failure during ICU stay. A statistical analysis was performed to evaluate the association of patient characteristics with extubation outcome, and a Poisson regression model determined the predictive value. Results: Seventy-seven patients were extubated; the mean age was 57.2 years, 52.5% were male, and their mean APACHE II score at admission was 17.8. On average, MV duration until extubation was 8.7 ± 3.7 days, with 14.9 ± 10.1 days of ICU stay and 24.6 ± 14.0 days with COVID-19 symptoms. The rate of extubation failure (ie, the patient had to be reintubated during their ICU stay) was 22.1% (n = 17), while extubation was successful in 77.9% (n = 60) of cases. Failure was observed in only 7.8% of cases when evaluated 48 hours after extubation. The mean reintubation time was 4.28 days. After adjusting the analysis for age, sex, during of symptoms, days under MV, dialysis, and PaO2/FiO2 ratio, some parameters independently predicted extubation failure: age ≥ 66 years (APR = 5.12 [1.35-19.46]; p = 0.016), ≥ 31 days of symptoms (APR = 5.45 [0.48-62.19]; p = 0.016), and need for dialysis (APR = 5.10 [2.00-13.00]; p = 0.001), while a PaO2/FiO2 ratio >300 decreased the probability of extubation failure (APR = 0.14 [0.04-0.55]; p = 0.005). The presence of three predictors (ie, age ≥ 66 years, time of symptoms ≥ 31 days, need of dialysis, and PaO2/FiO2 ratio < 200) increased the risk of extubation failure by a factor of 23.0 (95% CI, 3.34-158.5). Conclusion: COVID-19 patients had an extubation failure risk that was almost three times higher than non-COVID-19 patients, with the extubation of the former being delayed compared to the latter. Furthermore, an age ≥ 66 years, time of symptoms ≥ 31 days, need of dialysis, and PaO2/FiO2 ratio > 200 were independent predictors for extubation failure, and the presence of three of these characteristics increased the risk of failure by a factor of 23.0.

Clinical and Radiological Characteristics of Children and Adults With First-Attack Myelin Oligodendrocyte Glycoprotein Antibody Disease and Analysis of Risk Factors for Predicting the Severity at Disease Onset in Central China.

Objective: To analyze and compare different clinical, laboratory, and magnetic resonance imaging characteristics between pediatric and adult patients with first-attack myelin oligodendrocyte glycoprotein antibody disease (MOGAD) and to explore predictive factors for severity at disease onset. Methods: Patients diagnosed with MOGAD at the First Affiliated Hospital of Zhengzhou University from January 2013 to August 2021 were enrolled in this retrospective study. Age at disease onset, sex, comorbidities, laboratory tests, magnetic resonance imaging (MRI) characteristics, and Expanded Disability Status Scale (EDSS) scores were collected and analyzed. The association between risk factors and initial EDSS scores at disease onset was analyzed using logistic regression models and Spearman correlation analyses. A receiver-operating characteristic (ROC) curve analysis was used to evaluate the predictive ability of the uric acid and homocysteine (Hcy) levels for the severity of neurological dysfunction at the onset of MOGAD. Results: Sixty-seven patients (female, n=34; male, n=33) with first-attack MOGAD were included in this study. The mean age at onset was 26.43 ± 18.22 years (range: 3-79 years). Among patients <18 years of age, the most common presenting symptoms were loss of vision (36.0%), and nausea and vomiting (24.0%), and the most common disease spectrum was acute disseminated encephalomyelitis (ADEM) (40.0%). Among patients aged ≥18 years, the most common presenting symptoms were loss of vision (35.7%), paresthesia (33.3%), and paralysis (26.2%), and the most common disease spectrum was optic neuritis (35.7%). The most common lesions were cortical gray matter/paracortical white matter lesions in both pediatric and adult patients. Uric acid [odds ratio (OR)=1.014; 95% confidence interval (CI)=1.006-1.022; P=0.000] and serum Hcy (OR=1.125; 95% CI=1.017-1.246; P=0.023) levels were significantly associated with the severity of neurological dysfunction at disease onset. Uric acid levels (r=0.2583; P=0.035) and Hcy levels (r=0.3971; P=0.0009) were positively correlated with initial EDSS scores. The areas under the ROC curve were 0.7775 (95% CI= 0.6617‒0.8933; P<0.001) and 0.6767 (95% CI=0.5433‒0.8102, P=0.014) for uric acid and Hcy levels, respectively. Conclusion: The clinical phenotype of MOGAD varies in patients of different ages. The most common disease spectrum was ADEM in patients aged<18 years, while optic neuritis was commonly found in patients aged ≥18 years. The uric acid and Hcy levels are risk factors for the severity of neurological dysfunction at disease onset in patients with first-attack MOGAD.

Diabetes as a predictive factor for severe form and high mortality risk of COVID-19: Retrospective cohort study of 188 cases.

INTRODUCTION: Since the appearance of the first case of the SARS CoV 2 infection, several studies have been conducted to identify the predictive factors of mortality in patients with COVID-19. According to previous reports, diabetes seems to be associated with severe clinical forms of the new coronavirus (SARS CoV 2).Our study aimed to identify the epidemiological, clinical, radiological and prognostic profile of diabetic patients with COVID-19. METHODS: This retrospective study included diabetic patients diagnosed with COVID-19 and admitted to the Resuscitation Department of our university hospital center From Mars 1st 2020, to December 31st, 2020. RESULTS AND DISCUSSION: In this study, we collected the data of 600 patients admitted to the Anesthesia and Resuscitation Department of the Mohammed VI University Hospital of Oujda, a group of 188 (31.3%) had diabetes.The median age of our patients was 67 [25-75]. Were noted in the majority, of patients 69.6% with diabetes have developed a severe or critical injuries in the Chest CT Scan. Furthermore, we found that the mortality rate in this category of patients was higher 65/188 (34.60%) compared to non-diabetic patients, 130/412 (31.60%) (34.60%vs 31.60%; p: 0.464). CONCLUSION: Based on the results of this retrospective study, we concluded that diabetes is predictive factor for the need of an intensive care as well as a high risk of mortality related to COVID-19.Practically speaking, diabetic patients should be monitored more closely and need an aggressive preventive management protocols in order to prevent severe forms of the disease and a drastic evolution.More research is direly needed to identify patients of a higher risk of developing severe forms of COVID-19.

The Abnormal Imaging of SARS-CoV-2: A Predictive Measure of Disease Severity.

To investigate the characteristics of SARS-CoV-2 pneumonia and evaluate whether CT scans, especially at a certain CT level, could be used to predict the severity of SARS-CoV-2 pneumonia. In total 118 confirmed patients had been enrolled. All data including epidemiological, clinical characteristics, laboratory results, and images were collected and analyzed when they were administrated for the first time. All patients were divided into two groups. There were 106 severe/critical patients and 12 common ones. A total of 38 of the patients were women. The mean age was 50.5 ± 11.5 years. Overall, 80 patients had a history of exposure. The median time from onset of symptoms to administration was 8.0 days. The main symptoms included fever, cough, anorexia, fatigue, myalgia, headaches, and chills. Lymphocytes and platelets decreased and lactate dehydrogenase increased with increased diseased severity (P < 0.05). Calcium and chloride ions were decreased more significantly in severe/critical patients than in common ones (P < 0.05). The main comorbidities were diabetes, chronic cardiovascular disease, and chronic pulmonary disease, which occurred in 47 patients. In all 69 patients had respiratory failure, which is the most common SARS-CoV-2 complication, and liver dysfunction presented in 37 patients. Nine patients received mechanical ventilation therapy. One patient received continuous blood purification and extracorporeal membrane oxygenation (EMCO) treatments. The average stay was 18.1 ± 10.8 days. Four patients died. The median of the radiographic score was four in common, and five in the severe/critical illness, which was a significant difference between the two groups. The radiographic score was in negative correlation with OI (ρ = -0.467, P < 0.01). The OI in severe/critically ill cases decreased significantly as the disease progressed, which was related to the lesion area in the left lung and right lungs (ρ = 0.688, R = 0.733). OI, the lesion area in the left lung and right lungs, lymphocytes, etc. were associated with different degrees of SARS-CoV-2 pneumonia (P < 0.05). The lesion area in both lungs were possible predictive factors for severe/critical cases. Patients with SARS-CoV-2 pneumonia showed obvious clinical manifestations and laboratory result changes. Combining clinical features and the quantity of the lesion area in the fourth level of CT could effectively predict severe/critical SARS-CoV-2 cases.

Development and validation of nomogram to predict severe illness requiring intensive care follow up in hospitalized COVID-19 cases.

BACKGROUND: Early identification of severe COVID-19 patients who will need intensive care unit (ICU) follow-up and providing rapid, aggressive supportive care may reduce mortality and provide optimal use of medical resources. We aimed to develop and validate a nomogram to predict severe COVID-19 cases that would need ICU follow-up based on available and accessible patient values. METHODS: Patients hospitalized with laboratory-confirmed COVID-19 between March 15, 2020, and June 15, 2020, were enrolled in this retrospective study with 35 variables obtained upon admission considered. Univariate and multivariable logistic regression models were constructed to select potential predictive parameters using 1000 bootstrap samples. Afterward, a nomogram was developed with 5 variables selected from multivariable analysis. The nomogram model was evaluated by Area Under the Curve (AUC) and bias-corrected Harrell's C-index with 95% confidence interval, Hosmer-Lemeshow Goodness-of-fit test, and calibration curve analysis. RESULTS: Out of a total of 1022 patients, 686 cases without missing data were used to construct the nomogram. Of the 686, 104 needed ICU follow-up. The final model includes oxygen saturation, CRP, PCT, LDH, troponin as independent factors for the prediction of need for ICU admission. The model has good predictive power with an AUC of 0.93 (0.902-0.950) and a bias-corrected Harrell's C-index of 0.91 (0.899-0.947). Hosmer-Lemeshow test p-value was 0.826 and the model is well-calibrated (p = 0.1703). CONCLUSION: We developed a simple, accessible, easy-to-use nomogram with good distinctive power for severe illness requiring ICU follow-up. Clinicians can easily predict the course of COVID-19 and decide the procedure and facility of further follow-up by using clinical and laboratory values of patients available upon admission.

Assessment of the Health-Promoting Behaviors of Hospitalized Patients with Non-Communicable Diseases During the Second Wave of COVID-19.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has affected the health-related behaviors of patients with non-communicable diseases (NCDs). Thus, the factors predicting the health-promoting behaviors (HPBs) of hospitalized patients with NCDs during the second wave of COVID-19 should be examined. OBJECTIVE: The aims of this study were to determine the relationships among the patients' characteristics, perceived self-efficacy, social support, perception of the benefits of and barriers, and HPBs, and to determine the predictive factors of HPBs among hospitalized patients with NCDs during the second wave of COVID-19. PATIENTS AND METHODS: The study had a cross-sectional predictive correlational design and included 250 patients with NCDs 18 years of age or older hospitalized in a tertiary hospital in Thailand. Descriptive statistics, the chi-square test, the Pearson's correlation coefficient, and stepwise multiple linear regression were used for data analysis. RESULTS: Most of the participants had a cardiovascular disease (34.0%). Followed by diabetes (28.8%), cancer (11.2%), hypertension (10.0%), heart disease (9.6%), or chronic obstructive pulmonary disease (6.4%) and had a moderate level of overall HPBs (M = 106.09; SD = 4.66). Among the six components of the HPBs, the participants achieved the moderate levels in nutrition, interpersonal relations, spiritual growth, and stress management, and low levels in physical-activity and health responsibility. The patients' perception of the benefits and barriers to the adoption of HPBs and perceived self-efficacy and social support were able to predict their HPBs, accounting for approximately 38.0% of the variance of such behaviors. CONCLUSION: On the basis of our study's results, we suggest that researchers, multidisciplinary teams, the government, and policymakers establish effective interventions, guidelines, and policies for the development of HPBs to prevent and control the spread of COVID-19 particularly among patients with NCDs, and to improve their capacity for high-quality and continuing self-care.

Low CD4 T cell count predicts radiological progression in severe and critically ill COVID-19 patients: a case control study.

BACKGROUND: Novel coronavirus disease (COVID-19) has spread globally and caused over 3 million deaths, posing great challenge on public health and medical systems. Limited data are available predictive factors for disease progression. We aim to assess clinical and radiological predictors for pulmonary aggravation in severe and critically ill COVID-19 patients. METHODS: Patients with confirmed COVID-19 in Renmin Hospital of Wuhan University, China, between Feb. 6th, 2020 and Feb. 21st, 2020 were retrospectively collected. Enrolled patients were divided into non-progression group and progression group based on initial and follow-up chest CTs. Clinical, laboratory, and radiological variables were analyzed. RESULTS: During the study period, 162 patients were identified and a total of 126 patients, including 97 (77.0%) severe cases and 29 (23.0%) critically ill cases were included in the final analysis. Median age was 66.0 (IQR, 56.0-71.3) years. Median time from onset to initial chest CT was 15.0 (IQR, 12.0-20.0) days and median interval to follow-up was 7.0 (IQR, 5.0-7.0) days. Compared with those who did not progress (n=111, 88.1%), patients in the progression group (n=15, 11.9%) had significantly higher percentage of peak body temperature >38 °C (P=0.002), lower platelet count (P=0.011), lower CD4 T cell count (P=0.002), lower CD8 count (P=0.011), higher creatine kinase level (P=0.002), and lower glomerular filtration rate (P=0.018). On both univariate and multivariable analysis, only CD4 T cell count <200/µL was significant (OR, 6.804; 95% CI, 1.450-31.934; P=0.015) for predicting pulmonary progression. CONCLUSIONS: Low CD4 T cell count predicts progression of pulmonary change in severe and critically ill patients with COVID-19.

Health screening program revealed risk factors associated with development and progression of papillomacular bundle defect.

BACKGROUND/AIMS: The papillomacular bundle (PMB) area is an important anatomical site associated with central vision. As preventive medicine and health screening examinations are now becoming commonplace, the incidental detection of papillomacular bundle defect (PMBD) on fundus photography has been increasing. However, clinical significance of incidental PMBD has not been well documented to date. Thus, through long-term and longitudinal observation, we aimed to investigate the risk factors for the development and progression of PMBD and its predictive role associated with systemic diseases and glaucoma. METHODS: This longitudinal study included subjects who had undergone standardized health screening. We retrospectively reviewed patients for whom PMBD had been detected in fundus photography and followed up for more than 5 years. For a comparative analysis, non-PMBD groups of age- and gender-matched healthy controls were selected. RESULTS: A total of about 67,000 fundus photographs were analyzed for 8.0 years, and 587 PMBD eyes were found. Among them, 234 eyes of 234 patients who had had fundus photographs taken for more than 5 years were finally included. A total of 216 eyes (92.3%) did not progress during the 8.1 ± 2.7 years, whereas 18 eyes (7.7%) showed progression at 7.6 ± 2.9 years after initial detection. A multivariate logistic regression analysis using 224 non-PMBD healthy controls revealed low body mass index (BMI < 20 kg/m2), systemic hypertension, and sclerotic changes of retinal artery as the significant risk factors for the development of PMBD. Regarding PMBD progression, low BMI, concomitant retinal nerve fiber layer defect (RNFLD) at non-PMB sites, optic disc hemorrhage, and higher vertical cup/disc ratio were individual significant risk factors. CONCLUSION: PMBD is associated with ischemic effects. Although the majority of PMBD do not progress, some of cases are associated with glaucomatous damage in a long-term way. PMBD might be a personalized indicator representing ischemia-associated diseases and a predictive factor for diagnosis and preventive management of glaucoma.

Proteinuria as a Biomarker for COVID-19 Severity.

BACKGROUND: Renal involvement in syndrome coronavirus 2 (SARS-CoV-2) infection has been retrospectively described, especially acute kidney injury (AKI). However, quantitative proteinuria assessment and its implication in coronavirus disease 2019 (COVID-19) remain unknown. METHODS: In this prospective, multicenter study in France, we collected clinical and biological data including urinary protein to creatine ratio (UPCR) in patients presenting with moderate to severe COVID-19. Clinical outcome was analyzed according to the level of UPCR. RESULTS: 42/45 patients (93.3%) had renal involvement (abnormal urinary sediment and/or AKI). Significant proteinuria occurred in 60% of patients. Urine protein electrophoresis showed tubular protein excretion in 83.8% of patients with proteinuria. Inflammatory parametersand D-dimer concentrations correlated with proteinuria level. Patients who required intensive care unit (ICU) admission had higher proteinuria (p = 0.008). On multivariate analysis, proteinuria greater than 0.3 g/g was related to a higher prevalence of ICU admission [OR = 4.72, IC95 (1.16-23.21), p = 0.03], acute respiratory distress syndrome (ARDS) [OR = 6.89, IC95 (1.41-53.01, p = 0.02)], nosocomial infections [OR = 3.75, IC95 (1.11-13.55), p = 0.03], longer inpatient hospital stay (p = 0.003). CONCLUSION: Renal involvement is common in moderate to severe SARS-CoV-2 infection. Proteinuria at baseline is an independent risk factor for increased hospitalization duration and ICU admission in patients with COVID-19.

Analysis of the predictive factors for a critical illness of COVID-19 during treatment － relationship between serum zinc level and critical illness of COVID-19.

OBJECTIVES: Because most severely ill patients with COVID-19 in our hospital showed zinc deficiency, we aimed to examine the relationship between the patient's serum zinc level and severe cases of COVID-19. METHODS: Serum zinc <70 µg/dL was defined as the criterion for hypozincemia, and patients continuously with serum zinc <70 µg/dL were classified in the hypozincemia cohort. To evaluate whether hypozincemia could be a predictive factor for a critical illness of COVID-19, we performed a multivariate analysis by employing logistic regression analysis. RESULTS: Prolonged hypozincemia was found to be a risk factor for a severe case of COVID-19. In evaluating the relationship between the serum zinc level and severity of patients with COVID-19 by multivariate logistic regression analysis, critical illness can be predicted through the sensitivity and false specificity of a ROC curve with an error rate of 10.3% and AUC of 94.2% by only two factors: serum zinc value (P = 0.020) and LDH value (P = 0.026). CONCLUSIONS: Proper management of the prediction results in this study can contribute to establishing and maintaining a safe medical system, taking the arrival of the second wave, and the spread of COVID-19 in the future into consideration.

Predictors of Severity in Covid-19 Patients in Casablanca, Morocco.

Background Morocco was affected, as were other countries, by the coronavirus disease 2019 (COVID-19) pandemic. Many risk factors of COVID-19 severity have been described, but data on infected patients in North Africa are limited. We aimed to explore the predictive factors of disease severity in COVID-19 patients in a tertiary hospital in Casablanca. Methods In this single-center, retrospective, observational study, we included all adult patients with confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, admitted to Sheikh Khalifa International University Hospital in Casablanca between March 18 and May 20, 2020. Patients were separated into two groups: Non-severe patients were those with mild or moderate forms of COVID-19, and severe patients were those admitted to the intensive care unit (ICU) who had one of the following signs-respiratory rate > 30 breaths/min; oxygen saturation < 93% on room air; acute respiratory distress syndrome (ARDS); or required mechanical ventilation. Demographic, clinical, laboratory data, and outcomes were reviewed. We used univariable and multivariable logistic regression to explore predictive factors of severity. Results We reported 134 patients with confirmed SARS-CoV-2 infection. The median age was 53 years (interquartile range [IQR], 36-64), and 73 (54.5%) were men. Eighty-nine non-severe patients (66.4%) were admitted to single bedrooms, and 45 (33.6%) were placed in the ICU. The median time from illness onset to hospital admission was seven days (IQR, 3.0-7.2). Ninety-nine patients (74%) were admitted directly to the hospital, and 35 (26%) were transferred from other structures. Also, 68 patients (65.4%) were infected in clusters. Of the 134 patients, 61 (45.5%) had comorbidities, such as hypertension (n = 36; 26.9%), diabetes (n = 19; 14.2%), and coronary heart disease (n = 16; 11.9%). The most frequent symptoms were fever (n = 61; 45.5%), dry cough (n = 59; 44%), and dyspnea (n = 39; 29%). A total of 127 patients received hydroxychloroquine and azithromycin (95%). Eleven critical cases received lopinavir/ritonavir (8.2%). Five patients received tocilizumab (3.7%). We reported 13 ARDS cases in ICU patients (29%), eight with acute kidney injury (17.8%), and four thromboembolic events (8.8%). Fourteen ICU patients (31.1%) died at 28 days. In univariable analysis, older men with one or more comorbidities, infection in a cluster, chest scan with the COVID-19 Reporting and Data System (CO-RADS) 5, lymphopenia, high rates of ferritin, C-reactive protein (CRP), D-dimer, and lactate dehydrogenase were associated with severe forms of COVID-19. Multivariable logistic regression model founded increasing odds of severity associated with older age (odds ratio [OR] 1.05, 95% confidence interval [CI] 1.01-1.09, P = .0039), men (OR 3.19, CI 1.06-9.60, P = .016), one or more comorbidities (OR 4.36, CI 1.32-14.45, P = .016), CRP > 10 mg/L (OR 5.47, CI 1.57-19.10, P = .008), and lymphopenia lower than 0.8 x109/L (OR 6.65, CI 1.43-30.92, P = .016). Conclusions Clinicians should consider older male patients with comorbidities, lymphopenia, and a high CRP rate as factors to predict severe forms of COVID-19 earlier. The higher severity of infected patients in clusters must be confirmed by epidemiological and genetic studies.